The present invention relates to method and apparatus for processing image signals, program for the same and image-recording apparatus.
In recent years, when conducting the development or the printing operation for a photographic image, the image formed on the color film has been converted to the image signals by photo-electronically reading the image with the CCD (Charge Coupled Device) sensor, etc. Various kinds of image processing, represented by the negative/positive inversion processing, the luminance adjustment processing, the color balance adjustment processing, the granularity eliminating processing and the sharpness enhancing processing, are applied to such the image signals, and then, the processed image signals are distributed to the viewers by means of the storage medium, such as a CD-R, a floppy (Registered Trade Mark) disk, a memory card, etc. or through the Internet. Each of the viewers would view the hard-copy image printed by anyone of an ink-jetting printer, a thermal printer, etc., or the image displayed on one of various kinds of display devices including a CRT (Cathode Ray Tube), a liquid-crystal display device, a plasma display device, etc., based on the distributed image signals.
Generally speaking, the image on the color film is formed by gathering dye-clouds having various sizes. Accordingly, when the image formed on the color film is enlarged for observation, mottled granular irregularity becomes visible corresponding to the sizes of dye-clouds, at an area where a color pattern should be inherently uniform. Owing to this fact, the image signals, acquired by photo-electronically reading the image formed on a photographic film with the CCD sensor or the like, includes granular noises corresponding to the mottled granular irregularity. It has bee a problem that the abovementioned granular noises considerably increase, especially associated with the image processing for enhancing the sharpness of the image, and deteriorate the image quality.
In recent years, a less costly digital still camera (hereinafter abbreviated as “DSC”) has come into widespread use. The DSC incorporated in such equipment as a cellular phone and laptop PC is also extensively used. The image sensor used in a less-costly DSC is characterized by a small pixel pitch. Shot noise tends to be produced at a low sensitivity, and not much consideration is given to cooling of an image sensor, so that conspicuous dark current noise is produced. The CMOS image sensor is often adopted in the less-costly DSC, so leakage current noise is conspicuous. When such noise is further subjected to image processing of interpolation of color filter arrangement and edge enhancement, the mottled granular irregularities are formed to deteriorate image quality. This has raised a problem (for DSC noise and interpolation of color film arrangement, refer to, for instance, “Digital Photography” Chapter 2 and 3, published by The Society of Photographic Science and Technology of Japan, Corona Publishing Co., Ltd.).
Further, the low-pass filter median filter technique has been well-known as a method for solving the abovementioned problem (for instance, refer to “Practical Image Processing learnt in C-language” P54, by Inoue et al., Ohm Publishing Co., Ltd.). However, noise removal by simple filtering involves reduced image sharpness, and a satisfactory image cannot be obtained.
To solve the abovementioned problems, application of an image processing employing the Dyadic Wavelet transform, which is capable of accurately eliminating various kinds of noises, could be possibly considered (for instance, refer to Non-Patent Document 1). The image processing employing the Dyadic Wavelet transform has bee used for, for instance, the sharpness change of the image, the contrast change of the image, etc.
Non-Patent Document 1: “Singularity detection and processing with wavelets” by S. Mallat and W. L. Hwang, IEEE Trans. Inform. Theory 38 617 (1992)
There has been a problem, however, that the processing velocity becomes slow in the abovementioned image processing employing the Dyadic Wavelet transform, since the processing load would be getting heavy according as increase of its conversion levels and the image size of the image signals (namely, increase of the pixels, increase of data amount of the image signals). In other words, since the Dyadic Wavelet transform of a single level decomposes the original image into three different images including an image of low frequency band component, an image of high frequency band component in the direction of “x” and an image of high frequency band component in the direction of “y”, each of which has the same image size as that of the original image, the total image size of the converted images becomes larger than that of the original image, resulting in a heavy processing load.